{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 401 CNN\n",
    "\n",
    "View more, visit my tutorial page: https://mofanpy.com/tutorials/\n",
    "My Youtube Channel: https://www.youtube.com/user/MorvanZhou\n",
    "\n",
    "Dependencies:\n",
    "* torch: 0.1.11\n",
    "* torchvision\n",
    "* matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "from torch.autograd import Variable\n",
    "import torch.utils.data as Data\n",
    "import torchvision\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<torch._C.Generator at 0x7f33c006fe50>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "torch.manual_seed(1)    # reproducible"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Hyper Parameters\n",
    "EPOCH = 1               # train the training data n times, to save time, we just train 1 epoch\n",
    "BATCH_SIZE = 50\n",
    "LR = 0.001              # learning rate\n",
    "DOWNLOAD_MNIST = True   # set to False if you have downloaded"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz\n",
      "Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz\n",
      "Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz\n",
      "Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz\n",
      "Processing...\n",
      "Done!\n"
     ]
    }
   ],
   "source": [
    "# Mnist digits dataset\n",
    "train_data = torchvision.datasets.MNIST(\n",
    "    root='./mnist/',\n",
    "    train=True,                                     # this is training data\n",
    "    transform=torchvision.transforms.ToTensor(),    # Converts a PIL.Image or numpy.ndarray to\n",
    "                                                    # torch.FloatTensor of shape (C x H x W) and normalize in the range [0.0, 1.0]\n",
    "    download=DOWNLOAD_MNIST,                        # download it if you don't have it\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([60000, 28, 28])\n",
      "torch.Size([60000])\n"
     ]
    },
    {
     "data": {
      "image/png": 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J35O0toY+vsL25MYXMbI9WdK31X9Tj6+VtLBxf6Gkp2rs5U/0y7TtzaaVV83vXb9Nd1/LGX6NoYx/kzRJ0sMRsaznTYzB9iyN7O2lkcudf1Znb7bXSLpII5d8bpd0u6T/kPSYpFMlvSfp+ojo+RdvTXq7SIc4bXuXems2rfwG1fjeVTndfSX9cHovkBNn+AFJEX4gKcIPJEX4gaQIP5AU4QeSIvxAUv8PrRppPyv+BEQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f33a14e6518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot one example\n",
    "print(train_data.train_data.size())                 # (60000, 28, 28)\n",
    "print(train_data.train_labels.size())               # (60000)\n",
    "plt.imshow(train_data.train_data[0].numpy(), cmap='gray')\n",
    "plt.title('%i' % train_data.train_labels[0])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data Loader for easy mini-batch return in training, the image batch shape will be (50, 1, 28, 28)\n",
    "train_loader = Data.DataLoader(dataset=train_data, batch_size=BATCH_SIZE, shuffle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert test data into Variable, pick 2000 samples to speed up testing\n",
    "test_data = torchvision.datasets.MNIST(root='./mnist/', train=False)\n",
    "test_x = Variable(torch.unsqueeze(test_data.test_data, dim=1)).type(torch.FloatTensor)[:2000]/255.   # shape from (2000, 28, 28) to (2000, 1, 28, 28), value in range(0,1)\n",
    "test_y = test_data.test_labels[:2000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "class CNN(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(CNN, self).__init__()\n",
    "        self.conv1 = nn.Sequential(         # input shape (1, 28, 28)\n",
    "            nn.Conv2d(\n",
    "                in_channels=1,              # input height\n",
    "                out_channels=16,            # n_filters\n",
    "                kernel_size=5,              # filter size\n",
    "                stride=1,                   # filter movement/step\n",
    "                padding=2,                  # if want same width and length of this image after con2d, padding=(kernel_size-1)/2 if stride=1\n",
    "            ),                              # output shape (16, 28, 28)\n",
    "            nn.ReLU(),                      # activation\n",
    "            nn.MaxPool2d(kernel_size=2),    # choose max value in 2x2 area, output shape (16, 14, 14)\n",
    "        )\n",
    "        self.conv2 = nn.Sequential(         # input shape (1, 28, 28)\n",
    "            nn.Conv2d(16, 32, 5, 1, 2),     # output shape (32, 14, 14)\n",
    "            nn.ReLU(),                      # activation\n",
    "            nn.MaxPool2d(2),                # output shape (32, 7, 7)\n",
    "        )\n",
    "        self.out = nn.Linear(32 * 7 * 7, 10)   # fully connected layer, output 10 classes\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = self.conv1(x)\n",
    "        x = self.conv2(x)\n",
    "        x = x.view(x.size(0), -1)           # flatten the output of conv2 to (batch_size, 32 * 7 * 7)\n",
    "        output = self.out(x)\n",
    "        return output, x    # return x for visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CNN(\n",
      "  (conv1): Sequential(\n",
      "    (0): Conv2d(1, 16, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n",
      "    (1): ReLU()\n",
      "    (2): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "  )\n",
      "  (conv2): Sequential(\n",
      "    (0): Conv2d(16, 32, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n",
      "    (1): ReLU()\n",
      "    (2): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
      "  )\n",
      "  (out): Linear(in_features=1568, out_features=10, bias=True)\n",
      ")\n"
     ]
    }
   ],
   "source": [
    "cnn = CNN()\n",
    "print(cnn)  # net architecture"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "optimizer = torch.optim.Adam(cnn.parameters(), lr=LR)   # optimize all cnn parameters\n",
    "loss_func = nn.CrossEntropyLoss()                       # the target label is not one-hotted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/yoshitaka-i/.conda/envs/tensor/lib/python3.5/site-packages/ipykernel_launcher.py:29: UserWarning: invalid index of a 0-dim tensor. This will be an error in PyTorch 0.5. Use tensor.item() to convert a 0-dim tensor to a Python number\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch:  0 | train loss: 2.3101 | test accuracy: 0.20\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3344d2df60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch:  0 | train loss: 0.6699 | test accuracy: 0.88\n"
     ]
    },
    {
     "data": {
      "image/png": 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eXdOeY8YZ/Mc/aZ9BNnBF+EWkiKjoz1FKPRPbvElE9lRKfSkiewKbjc5VSs0AZgCMGjVK/8W5Qd++puq/2+09Gyexnv8I4Bex7RMBo3boyd22rMS/r/z0RlNjimypY78xt3fYtorozOJ1XHjBmPzZGp6XQ3TrVsr487/FT8fPpKWljUuvOoFImmqtZp3BV136NPVfN/HL/z2Www4fYnjMyrU3tX/W4Z32cCOqR4g2cfpQKXVHwq55RDXglti/zzu9l8Yk1dWmunA57T3r5KURx+3499Y9yjtts5RglUmgdRetdk7/wSGc/oNDTB2b6AxOJ+y33nGGJZ+BUXin3dpC+fQScWPGfwQwAfiviCyLbbuO6N/xkyIyGdgAnOXCvTRmiQtU0h9OfPb7dtYHZEy24t9NvWC0icczzDqDyytKKK8oafcZ9Ord+UWeCbux/vmUI+BGVM/bQKrX8vFOr69xl/jsNx2pWjJC5uboVsmWCy8fE6yCRKIzOJ2wW/EZaOyjq3PmIanCMqfF/nXDhBM05hO18f8NHV7mBweNHMD6z7bS0tLKrrrGlMJeWBihrLwL/3htalqfgcYZumRDHnIinWfa8Zh6N6hZvYFnDpnAKa/cTb8jzdmAzeJlmYDJLQvaP3ejiDsLR7t27XzHqjNY4y1a+PMQI/OKm/V4lk2fRb+xI1262m6yWSZgJ82eXj9MRCJlrti/rTiDvUCXft6NFv4c5dKWReykmYdMHp8YU++ELYtWUdqvJ+LybO6AvW8E4F2AQ25u397cu4zV713p6r00HUkV6ZIYVhk0XvjW5TR+1dkxfFL8w3vwVOd6hLzUF67Ig8AtvdbKUazOWM3U4wHY3qsy7f5lN8/i4KvOs3RvJxR9lT+RGPmAW5m7RqJvhl02UjTCiJ7xa9qJhzxOTnPM4SeN4evqr/jmryZ1SoD6/MV36H3YfpSkeDnU9O3pak9fN6np29PvIWjQmbvZQgt/LvHMhdBQA7DbxDPnHONjz32806Z4yOOwFJfPZMbZuvwTqt98n3+++1+2r1hLzcfrOXbubygfEn1FXFY1Lzo2l0NC3SA+No2/zdXNZO5qnKOFP5eIib5d4ovrVDP+ZTfP4qgHr2PRlfca7h957cRoMxfgrUnT2XfSae2iH0YSo3wykUtRQH6J/rZtuyxn7mrsoYVfY4rPX3yHYx6dRlF5V8Y+bFSJpyPpjpncbJw3bLQSiPf6LSbqfD7Y3HCzjlWfypyWZ6inwdI5pZRwbuEZls4JCwveWsO855Zz6x0/dJy5m473mclSZiAIp3AP/TnU1euHBS38TkgwrViipBLOuN/98XjI1uWfMOjU77h2PTOx/k7q9Se/MB5Jk43sB1ZF3+45YcFOtU+r1LOd97ibC1hILRt5hglMDkzxkuyihd8Jdk0rDk0yfhA34biFmVj/VPX6M7n+jF4Ye2VB9HUCmH3MJngppWybf6p4jyEcRSHF9GAYTdTRQiOFGX+jcg8t/DnOqqoaLpq5BIDG5jZWV9ey9S/+mgvMxvrbrddv9MLYy8mAY1jJSA5jApifTl0wl+DlxPxTzzZK6NH+fQmV1LONCva0db0wo4U/x9l/YCVv3BCtlffkwg28vjIWqFxZAjX+mA4yOYnjWCqnnIDRC8MNKvcdzE/r33Tpav7Tyc8woH/Gc4paWxi18TMPR5UeJ+afUnrSwI727xuooZT8DOPVwp9H/HXBOq467RvRb+77fx32TT77YsBeqKWVmXBrY1PaWP9krNbrj2ypYz86vzDCwEUVP2HY6H0AGHPukRw16RhP72fHZ9Ac8VcynNT3Gci3eJ0baKWZWr6kmPK8NPOAFn7XMW1amftj8xd1wRm8tbaRj76o5Yh9ezu6jhFWavP8947H0sb6J2OmnHK8nEMiyc3hU4WoellQzirdB/Tkytdu8HUMuUAkUma4vZQeHM5FPMLRCMLJ3JXlkQUHLfwuk9K04gQXnMFPLNzAWd8a5HpctNXaPFZj/b2u1+9VQTk77KzewW3H/ZayXuWcfdt59B5qxrCVfYJe7CxdF61DmcShTMriaIKJrtVjl2cuzHjI2WMGc//kw7N2v3TMWbCe844wlwnZrXqr6es6qc0z9uHrfZ1lx19aZQPSV+i/45KrDbfXrN7AI6VHU/32clfGc/Oau7jy9V8x9mfHM2uKQQWxgHDnba/yxz/9iEfm/iRwoq8xh57x2yXbIZkO7rd2cx2NLa18Y4A5u3qqXrzJiVeZavPECWKJBjDvZK6s2Wl8vsurhYreFQAceOLBzJ0607XrWsGMn8FM71xNsNHCH8duMlYI2KtPOUt+d1LmAy2SqTZPkDH70kqF2+WnG+oaKC4tpiBSQNUHGyjv5W7GqlnM+BnM9M7VBBst/HFyVPS9JKi1ecyUeXD60jK7WjDLl6s28uhFD1FSUYKIMOG+dDVSvcOMn8FM71xNsNHCr3EFM/V7soHZMg9OXlpOVwtGDBu9N79e8vuMx9lNsopEytI6PePcvOYuKnpXsGL+B8ya8gCXz7+u0zHx3rlOSisk1uYBmHD2Q/zxvh9ZfoGkiuBp69tEwaZiy+Mq62v5lFCihd9FnGTJ+p1h+1DhEVm7VyaMirjFxTnRGdyteqth/Z3+7A7f3Iv0/QXA+kvLTxOX3cza1tZdrFx7U8YXgBk/gxu9c+3U5jlgr2mmr39TtXXRzye08LuIk1BOT8JArWAlr8Ahx2C90qaROPtVdC2oJi4zpHtxmPUzuNE7t1u3Uh5/dgoAheUR/vHaVEfX01hDC79HdMiSzda5JZWh8FU8irVKm0EmKCYuNwiKn0HjPVr4PcBJlqyjDNt02b1ZnNFnwkqlTU32MOtn0IQfLfwmsWKDd5Il61WGrRuksqlnOieZ5ZivtJmrlFJiqxGLRuMGWvhNYsUGP2fBeh78mb2MXSfnek2qxK44y4BrgZdIH1FzF+YrbdrBzfo73XZ4Yzqz20lrJf9Nvz9WTuH2u86isnup8TFrb4p+GDzc1hg04UcLvw3S2eCtZsm6da4dDFcxDq5ntnHKZZirtGmXTBm1D53/i/bPbUox6b0q1tQ20dimmDC0O1NHuFPIrseju18afUqEj8/q5sp1U9Hc1MKdt73KXff9iLLy4BrRgl7rJx/Qwm+RTDZ4J1mymc49YO3aDt/3ikR4a4j9dHnDVczrn9q+ntnGKTeRutKmU6xm1BaIMHPMII9Gs5vNDcrzeyx7v6q9nMKfHhjv+f0AzvnBDP76t8k0NrRw9ri/MG/+xWnDO8Pycsp1XBF+EXkYOA3YrJQ6MLatJ/AEMBRYB5ytlNruxv38JEg2+K2tra5dq30Vs3Sj7QYtZhun/M3GtTu1MhQxjPd3O6PWLg31Xq1nUrNlU217OQUzFLW2WK6vX9Ta0uF7qzH9iS8nXevHP9ya8c8E7gVmJ2y7BnhNKXWLiFwT+964zGGICLIN3i4dVjEJDVrizVnuGHg6lZu2mbqW1cYpZtlJc8eOUc1zOh3jRUZtnMQEt0QTTpA49fSDOPX0g0wf70YnLasx/YkvJ13rxz9cEX6l1FsiMjRp8ziiuToAs4A3CLnwZ9sG7wgLRecyrWIuq5rXaVuqiptmGqfYJVMUTJiLxmULv+3rld1Lda2fAOCljb+vUupLAKXUlyJiWPRcRKYAUwAGDx7s4XAyM6L1VjZTyfaI8VLZqyqXnmAhkcvNVYzXjVPS4VdGbcu65dQ/ehUUFCAFhZROvodIn6Ge39cqQbCv2ynVAKlr8mjs4btzVyk1A5gBMGrUKO89YGnYTHBn8tV1zZ5de8GN3/Xs2n7hakZtZfrchYLu/Si/4imktILm5fNpeOb3lF04w737u0QQ7OvdupWa8gtYqcujsY6Xwr9JRPaMzfb3BDZ7eK9AcMCY6R2+X7kws/ic/oe3uOq0b3DkiM5u0Pj1GlatYttzs+mfZX3uVr+LnaXZnWlVA9VvL/e2M9fcD1y9XEH3hJKOkWLExYbkt/eDXQkpI2faD7oKjH3djVo/Gmd4KfzzgIlEfXwTgec9vJdzSirBXuFD22QKDW2urqZq6lSaPvuM/rfemt3BAXe+8EjnjS40fjeKxgF4c+Jv+br6K75p8jrfZn3a/U0UsJQMoZq/OBZqrGUvbAc2Ffdkv+M7/kqrxl00PPVbuv7MPe/GLpO1+szY7rV9XRPHrXDOx4g6cnuLSBXRXhi3AE+KyGRgA3CWG/fyjDPuhyxHa/Sq6MLqP3wv5f7V6+6By4YDw4HX+Grpexx92LVZG58hHhWBc7ujFUAxbZkPsij6cfo2dYxyUi3N7Lp3El2+fymRAfvZuqZdzNrurdjX/3DLfJ1YlcO4FdWTqgLY8W5cP9tsUt3oK8Z9VlPRhjnTjhN6N9d13uhX8bW+fWGTe6WjgxJ/bwfV1sbX90+h6LDvUXzYaVm/v1nbvVn7OqBFP8fx3bkbRPZr+7/2z/2PMDcj9Fr03cZx45fq6ui/LtiHvYy/T6Zb9VYY6O41m5e8QPPy+bTt3EzTO08QGbg/Xc+/zd2bpMGK7d6sfX3p4vWmHL+ZnLDtdYE0gSK/hT8p1n27UbbRws6bvioq99/k4hDXGr+4MPP3Mv4+7ge4oOjc3RuVu8FjxaPHUTw6fQE7L/HCdn/jdfNccfxGImWWu4bp0E3vyW/ht2mvNjS5hBgnTWOornY867cbf39RxU8YNnofAMaceyRHTTrG0TgSuXjJRpZsq6dVwWUjevPjod1du7bb2I2NT4eZl4cZgTbT51eTffJb+D3GijnFz5678y4fm5X7AMz5/E9po3G+/fB5sU+7j0kVndN9QE+ufO0GawPom7mb9oodDaysaWThiftQ29zKyJfXWBb+j14b18kBzEsZTqrsBX+23pfMiu3eLKleHjq+PjfQwu8hVswpvvfczRL1/azPnFNF5+ys3sFtx/2Wsl7lnH3befQemqbCvwXzTv/SQooLhOY2RW1zGz2LrVcc6iT6ZrAZYQTux8a78fLQBBct/Db5YkFSNmcGbbBiTnFkeslRjFYJ9+542JN79SiOMLyimH3//jG7Wtp4YLSxN3j7S0d12mYU3x9GvnuS8e/fgy1zKaXEdiMZTTDQwp+EWZNLqno+Rljpo+uo565fuBza6TevVNexsb6FNaeNoKa5laNeXcvJe5bTxcQM2NZMP2RYbRmpCR5a+JPwwuRipYa/lWN7NdU6HpsruODgDRIK6FEUIVIgVBRFaGpTtFoIBJr5wCEw0NtuW37zYMvcTtv0SiA8aOFPg1smFyvVLzMdmypfwOxK5ZjfvZbxmGzjZXSOHU7oV85j63dw5Cuf0timuGTfXnQtNG/vvm55NeMMhD9MkUJ20CuB8KCFPwVumlzM1vB3Uu/f7EoliA5kq9E5Vl8UpZRYGo/Tdowrv7dvp20rdjTwm4P60rNLhj+58QcnbehYUK5hSxkle1gvKtVUEGHpwL0A+PaGTyyfr8kttPCnwM0Wi2Zr+LtV79/MSiVIDmRL0TlYe1FcUDg+VojtRhdGap/+pYWZRd8Efx9jPi5+QHNncwxEXwLFbdbbdjYVZL+dpMYbtPCnwIx5xpfY+/kfQVP6P9p5I3rBJ5ujX3GKI3BitHhY0BzIN6+5i4reFayY/wGzpjzA5fOvS3u81ReFkzBJt+hhIyTUK+Izf03+ogN1DTBrcombV9644XguPWUEZ422bx4wTQbRN3OeJw3jTSRGpaKidwUAB554MFs3fJXx+JvX3MWVr/+KsT87nllTHrB932zySnX2s73//fAboby2xnu08Btgx+Ty1wXrOO/Iod4MyGXmLFjPeUekLsB14UOLrV+0ujqaJJXpK4mGugbaWqMJWlUfbKC8V+b6MlZfFEHAbnWgshJ7z1fQt95TJ7nfDniNM7SpxwWCZjpJh5nVTNoXWIm7FTS/XLWRRy96iJKKEkSECfdNTnt8Q10DxaXFFEQKTL8ogsAJ/YzHmSnS54ofHGfYMcwonBLg4u6TGHLosKgZbJ0JM1gCQYuu0niHFn4X8MR0YhGzoYJmVjMpX2DjH3M6zE4MG703v17ye9PHW31RuMH8L2v585ptPHXE4PaErv+cvI+phK44BQa/G27UBErGqr8kEVu1jzTI3mXPAAAgAElEQVShRAu/C1iJ0/cCtwXEzxdYJqy+KNzAaUJXKtyoCZRMohls7tSZls79/Ud3OL6/Jhxo4XeIk9h7t/BCQAxJ7vblQv9dvzGzUnKa0JUKszWBOsf2wwWxf7+uLGPuPZcA4TWDabJPfgt/SaXjHrJmTCdbaxvpVZG6F6pTTAuI23jUfzdbmF0pOU3oSoWTmkBxutbsTubywwyWjC7lEA7yW/hTzVZd7mP7xMINXHTCcFvnJucKvHt4/07HWBWQsYdew9biCstj6dVUy1v/ucXyeUElayulFLhtQvLDDGYGXcoheOS38KfChZVAInMWrGfKcXtTaKO+eXIpBr7qXJjNqoDYEX0n5wUV31ZKMbwyIWk0mdDCb4TRSsDBKqCxpTWt6H+4scaUj+CvC9Zx9ohenbabFpDxj7m+mgkzbphanOCVCcksOnwzf9HCnwUy+QDMiH48VwAD4fdbQNwgLkLZDCf0KlrHbcbMX+NJRc9shm8m2/613d9ftPCbxWXzj1XiuQJe8+bSm601k4+vIBxG+DgVod8f8WuuW/AbS+eExdTiZpx/IpZrHrmItvv7ixZ+s6QTNTfMJxc9BzUNMOccw93tuQLvVzm7T4rM29baWjb89Kf0vmKEves6fCnGRejK139l63w7ESxhWSl55Xx2kuzlBgesXWv5nF6RCG8NSV1uRGMOLfxBoSb1DKhDroBT4T/jfjD4gysoK2Po44/DkmnOrm+TuAjZZdAhuSsGmZzPFxSON9w+p+WZtDNrJ8lefrG11WaRQk0HtPCHALfq9KdDCgqgwD8zhxPRT2T8Jfd0iG2HcIefbm9qte18PrfwjJQ1fXSyV36jhV/TTnN1tS/3TRQhp3QUfW/xupXiP7+s5Yn1NTw8ZmBG53Om2X0yXid76YihYOO58IvIycBdQAR4UCkV7imY3xRH7NXkr+wcDZRMUb9+sK7zdq8bziSK0C+fvoyynsGffXpRYC0ZK85nq85Sr5O9dMG31NzeD3bZ6Hpa1heucGlu5qnwi0gE+BNwAlAFLBaReUqpVV7eN1TEK16e+7i542NdtJLp0brb+bx9gvW6QW2NjRR0MS4rYbafr12siFBnU44/ZCPrNyzOZyP8jBgKOnZEP37eTQn1E528CLw26o4G1iil1iqlmoDHgXEe31Njg8bVq1l3jnFEUSJ+N5wJguhDx6zfkS9/wg0H9PF7SIEijF3SwobdFwh4L/wDgM8Tvq+KbWtHRKaIyBIRWbJlyxaPhxMCdtRbPmWT6ub4tqUHHRSN6kmD3w1nUkWv+EFi1u9H39uX65ZX0xjrJKYJZ5e0fMJrG79RYfcO7iml1AxgBsCoUaMCmDeZZX75PACrgCNm7/B3LEkEoeFMUAhL1q8f6Iih4OO18FcBiUbKgcAXHt8z+9jN6k3TxnB/oHzHJuq6W2ti3qfEO1H2u+FMkAhL1q8f2IkYiicQSnExbfX19LniCsqPOCILo/UGuw7cbOG18C8GhovIMGAjcA4QnPW6W3jUjOTzqdEs2hVEo9H/anTQnHOy0hDFrYYzpZTYStcvpSTlvsSwysUn7eNkeKbx0vE65+6Lqe9uYZacIlbfDMmz89m/eNBy6Ytk7EQMxRMIpbCQpg0bqJo6NdTCny3Rjzt7b0QddpNQPU3Rz8x5ngq/UqpFRC4G/kk0nPNhpdRKL++ZS5wItAC9iIZGGeJBH1wj3Eoic7swV3JYpVm8jsF3giXRd4jV2blX8fmJCYRtdXWU7GccvRYGbjclvZ5g2jzgeRy/UupF4EWv75OLzPfour0ikZxJfU8Oq6woyhxWmY0Y/LBgdXZ+X+1Mz8bSXF1N1dSpNH32Gf1vvdWz+3hNkE08cXTmbh7SXuQqB2rzJzdT2XzG/hnPyWbnrcbWtqzV9w87Rf36MezJJ2mqqmL9+PFUHHec4XGZirsJsGKvvTwYYe6ghV8TapKbqZjBdOetx/67+/OPD7I1Ph3pY47EBMJIeTkFZWW2r2X1R2613EWcotYWRm38DIBIpIz9hlxh+Rp+oYVfE2qSwyrNYKvzVn0zlBZZGtuuljbKXIz0yaX6N7taO/4sG1evZtP06VBQgGppoe8N2Sv3YLc3QHNkt3y2tnqfWPg+M1nKDAThFO6hP4favpYWfo07pAlN9ZLksEozUT22YvCf+6jj9yZWALZEP01Npb3/vYCCntH9S4AlG8xdsmtBEz8f+B/rY7HI+IEX0XWT+bDm/wG+6t2bo997z1QCYZhxKtr1bOc97uYCFlLLRp5hApN52/Z4tPAHhb59YZNFr1BfazH+nXCrq9i5j4Pyx6ZhJ6wycDH4cz/o+H2K8My46Fvl67ZiW+clYma1YUX04/T+ylpWr2prY93ZZ4cq3t8N0a7iPYZwFIUU04NhNFFHC40UYlxfKxNa+IOCHyWRk2P/c8DZa4YwFz9zymeLPu0QvnnOneebamITpGqbYYv3d0O069lGCT3avy+hknq2UcGetsakhV+jCQhj16+PhdmO8ewedssxB6XaZjbj/d3yqQznZIZzcvv3v2CZ5WuU0pMGdpdwaaCGUnp2Os5sEpcWfs1udtRD91Lr52hcIci5FXb7804DXgGKgbuBg10YS7bi/YO0yhnIt3idG2ilmVq+pJjyVCsGU/ZfLfya3fxmoXU/Azj3NQSVHx8Utb+Pd0OuvMFsjZs7NxivIsw6fu30510GLALeIVqi93zgX6bOTI/ZeH+nBGWVA1BKDw7nIh7haAThZO5ydD0t/Jrd+NR60RKVvaBmq9+jCAxOa9yYcfzarba5Gjgs9nkQ8BnQCDbdkVHcjPfPhN1VjlccyiQOZZIr19LCr3GVEX/byeYGaxE+fUqEj88y2VPgz0lzRi9n4ybaVfp9Dzds3omrgUsHL+y0325/3gOJmneagA+JlurdDp0M0P++8jSOenUt/zl5n065FAf87rn2z1MGLKUs0rx752Bg5TSg85gfbNm9rZQSWzWi7KxygsBNggI2pbP1a+EPELude+bpFYnsLsEQAKyKfvycHo/uDgW09CJwQnIYZTawcM9kM85ezz5reJzXNm+7DuH9iZbiPQHYGzgAMDKWPPPEDVwKPGqwb0rrUmZsjK4bOoi+BewkaHnRU8DNBCwTpLW/auEPEHace0F2CNrF0svDruknG7N5hySbcVKRLZu3HS6KfcVLi1utimRX7J1id5WTCrcTsJyihV8TSBJXAMl0WBEkm34Cztj1602v0JLNOEZk0+ZtB1OlxQOInVXOTWl6ILmdgGVyPEYzqE3TFP208GtChx1zkiNcdChbXaElmnFGLF7cab8bNW4+O/PMdnMSS6+2fH46vCotHjbcTsByQF/QM36Nx7SsW079o1dBQQFSUEjp5HuI9Bnq97CskU2HchKJZhwj3Khx09GclP3OqOMvuYeuNamLnF0Q+/fB2dcY7vezeN1Te08zdZzZBKxsoYU/wORCH9KC7v0ov+IppLSC5uXzaXjm95RdOMPvYYWCZDOOE+oWLEj5uyOFURloq6tj544GunVP3ebSC9KJvhmClGiVCgsJWFlBC7+PjJ/SwvZEU/bNHffnQh/SgsRm8ZFiJJIDv3I2TT9flVvr8pVsxhn25JOW7xln8223pfzdSTQn/fHWW6k4bkyHsE6j5C+jsE+/MJVolbhKq+yVdd+Q2wlYTsmBv8Lwsj1DMUOzMdqn/Kil/XOPSpg7I3j/rapxFw1P/ZauP0vt4guNWejP/zLsAuVkhTZ2/fpO29wsVZwuvt+NqKCGOns17d3AcqJV0ku7lBJbIZ+t1dZWRm4mYDkleAqh6YDVGO3tNbtfBEF5CaiWZnbdO4ku37+UyIDUAhR2s5DZFVqm1oFeUHHiiRmPcRIV9OWqjbbOcwO7iVa394v3x7We3BV2/FeFHKaTKScDg68dDEBreSsbr4/+ITmZjVm5t1eotja+vn8KRYd9j+LDTkt7bNjNQtmsHGkF1dpK9Y03pvzdWXfOOY47Xw0bvTdf9620XJO/jr6k8l5cvGQjS7bV06rgshG9DY9xkmjlZlP0xOSsySxw78Jp7mMmCSxVyGi4/rICjFWRT0ekLprmEvQYbTM0L3mB5uXzadu5maZ3niAycH+6nn9b2nPMmIXc4J7Gv1FqMUFoV2sRT1ePTrk/W5UjM5H4u9NWW5v2d8ctc9LcqvsyHrOxaHynbdMManau2NHAyppGFp64D7XNrYx8eQ3XGlzP7UQrOyQnZ2XrPmaSwFKFjOan8D9zob3OUyWVnZuXxPBidu1GjHai/T9ONk1AxaPHUTx6nOnjzZqF3MCq6EM0kzRdLH5Qsmj97GHrBv1LCykuEJrbFLXNbfQsNs75tZJodfuzr7OrIbZyeMytkXZOzvIKO0lgqUJG81P47bYbdKNNoQW86kMaBBOQEVbMQkEkSCs0p787u1qLfCuXANCjOMLwimL2/fvH7Gpp44HRA9ni8Jrtou8yyY1WFG0I9lp5/pmR/Iz3DMXcThJYqpdCfgq/Cca/fA/bGw3C757vPIPWuIMds1CQsDPLTowEGjrXuNeuH8QLo/nFK9V1bKxvYc1pI6hpbuWoV9dyqa8jMo8V0a9nO7M5gQt4N2N8v5tJYFr4U2Ao+hZZ/Oap7NzxPkOHX8Le+7tby3vA9AHtvoBcwapZyAucZIHamWUnRgKFCTsrgtbqEtPOSQX0KIoQKRAqiiI0tWW5TEeWsBLf72YSWLh+20LGQYfP4KtNr9FY777DJ9dEPyhkOws0MRIoEy3bt1NQVkZBcebmKV6TaUVw9t57ddoWdU4eb8o5eUK/ch5bv4MjX/mUxjbFJfsGv5qqXczG97uZBKaFP8aqqhoumrkEgMbmNrq7UCq7pOtA5xcJGX1KJPtF1FwkSO32kins0SPzQQHhyU/X0mVLhHFjdlciTeWcNKJAhJljBnXYNmdHHfXdrZeuKNlhXNkUouGR3+Qnlq/pF24lgTkSfhE5C7gR+AYwWim1JGHftcBkoBWYqpT6p5N7ec3+Ayt544bjAXhy4QYecTHGN59IbqBipyOXnwSt3Z5frNxr94zdbsJZ4x4do59SOSfNcu7UezMe06YUk96rYk1tE41tiglDu3NBihyAeHhkmITfLZzO+FcQTXv7S+JGEdkfOIdo053+wKsisq9SKlBdQ1I6cFPgpc0+mXgyV9gx6qSVrta+34S13V4YyEaFSqOVQiriKxA3yHJ3LcfYizmKoZT6UCn1scGuccDjSqlGpdRnwBogddaLT1h14B50+AxGHHwLQ/ad6tGInLH4zVN57fk9+XSV9TZ5YaJPSZqOFw5oqGugrbUNwLV2e2Zpra3lszPPZN348az9wQ+oW+Bd9qdVekXc8ScN5Fts4G1aaWYHG3yvUJm8ArF/nejK4Se8wRn8lZcIpj7E2ATe2fgH0LEDclVsWydEZAowBWDw4GDPcuM2+8JCc4KwYvHP2bF1IW1tjdRsW8qhRz7t5fA8dSYHge0TKj29vhtZoHbDM51UYvW6fPdbQ4a4Ul8oaBUqk1cgdvGju5ZZpikMZ0kZhV9EXgXDbu3XK6WeT3WawTZDQ69SagYwA2DUqFHhMQab4MDD/5L5IBcJojP50pZF7KRj2N8ZP05/TsMueHHegR6OyhizWaBfLOgcYVJQ1Ea/0dtth2c6qfNj5aVh9SUxdv16V/s6Gzkn6+p7UV5qs2+yg85o8fDIVJg13wSou5ZpMv52KqW+a+O6VUCioW0gfrT20fhOsuiboSR8JYloa46KtpXwzGTs1vmx8tKwurJwU/RT8YfnOtbGn5Y8/fvFscYC77AdZnwFYoSVujhWfBef8DJreIlTYquddJm6XuLIxp+GecA5ItJFRIYBw4FFHt3LFuNfvsfWeXsOOtvlkWhyjebqaj472/j3pLW2NuV58To/w559luobb7R1z/UTJ6YtwSwFBe2rkeLBg9nruecMjztg7Vpfykcb4lK/YyNShUZaCT214ruwE9lUz3a+5iuTT9SBlLGJTsM5fwDcA+wB/ENElimlTlJKrRSRJ4FVQAvwy6BF9NjNzI0Ulro8Ek2uERdwI1LV73Fa5ycoxeHcINm8tNLuheZ+0PF7C4XZrJhvrPgu7EQ2VfGeqVVCKnu+EY6EXyn1LPBsin3TgelOrq+xRradyflK3c3fT9kdLFHAjZAUZiAn1TSDVBzODbJhXsqEVYE2m1hlp+yCFz6E0GXu2q17H5RuVF6SbWeyE2pWb+CZQyZwyit30+/IQ/wejiW6nHpJyu5giQJuJarHSTXNsJdgTqSsb+ZjsoFXzdHtRDZ5kf8QOiW0W1I4sSUhPOraeDT2WDZ9Fv3GjvR1DPWtRZZr8u+sL4ZIUcruYF6V0k5Htu9pJTLoyU+N/QSJmcHJPGLCtZDcnevHQ50XVUzEy9BTq2UXvHgJhU74g0zVZ7NorN+YMqs30RRT3u0A30wxPbwNh8/IlkWrKO3XE4mkji0448crOm2bbFARuxtF3FloLzfwki5nGW5Pl1kc7Q52uu3uYJlMQX5gNcTTSc6BGxh15zIj/GV9rbVbDEpzdC9eQlr4s0hQTDF+m7yW3TyLox68jkVXZq69kgk74aJ2caM7WOPq1ZQedJDLI3OGVSF32lvYaSaw2e5cyVxRbbz9Jm8SwV3F7ZdQTgh/NmvopEI7Vs3x+Yvv0Puw/Sjp5fOyIwGzheSksIjyy59wdK+giT7YE3KzOQfpTDp2MerOpbFGTgj/4Ue/6PcQAjObDzpbl39C9Zvv8893/8v2FWup+Xg9x879DeVDjJLDs0OYqod6hdXkMT/DR426c528Zzld0pgONR3JCeG3QhBWB17y9suH+O5DSMfIaycy8tqJALw1aTr7TjrNV9HXRLEi5H6Hjxp152rV725L+Cr8p/yopRpoD+DaY++FCZE33pDrhcyOPHm530MwzdiHr894TJjDPsOCVSE3Gz7qVlXPZIy6c3UttD/bt+r0zQX8nvFnPWrXbiGzIKwUgjCGbBOEsE+r9IpEspaEZMWGnqoEg9U8ALPho28NGZLxGDtYqblvhmSnr5Gz9wPmspXVHMuNtu7Rqf5QCm6KAG3Wr69ow0oFHr+FPzTE/QgtLanbuHlNrq9WkjET9ukVLeuWU//oVVBQgBQUpszUTcSNrlV+4EfuQdhwUsLZSlLaNJvzBZHI0huNCyAbkjPekGw1ITFbi98Lglh22UuW3TyLg686z5d7F3TvR/kVT1Fx/UvtmbpOaWvcXeSrdccOPj3lFEfX88qUoulMciG2hzjS8LhpqvNXqjBSP8mZGX9YZsP5aK6xg99hnwXdE6ZpkeKUmbpWMGtS8SIEUuOMoDWRcUrOCL/Z2bDf8fZ+v6CynbXbjSJbSVZWwz7tNHXvUyKGPYETiWbq/jZjpq6ZdpBGJpXqRT3aa/nH6bEgc10SM2PXuEtQMnndIPDC7/YM2e94e6/NNS89Eaz/UrPlFCa3dOwxazXs004s/uYGlb48g4lMXavtII2E3g5Bzz1obXIvHfar8u70rrNoX6/s3CVNs5tgqYQBfs+Qg4TfqxW/MBP26TaqrY2v759C0WHfo/iw01Iel+rF0T9FxQM3RN8PWpuETYujFSFVWxtf3zeZwgOPpcsx56c+yV5Vi04cfc1MU8dpE5l5Ai/8+ebQTIffq5V8onnJCzQvn0/bzs00vfMEkYH70/X82/weli8k9xj2+mdjJxxWO7qtEXjhN0u+zoY13lA8ehzFo8fZPj9ZLOPN2P3ErqAmN8t2+rPJhFfx/5rd5Izw+zkbtuKH0C+o7GAnDt9LvDDxJJuZMjl87QpqD2w2wQgpdjN5g9JExgw5I/xu0tJSZyle34ofQptrskM8Dl9KK2hePj9lx6wgYvellc5ZraOAzBPEuHu3CbynacXin7Pu4zvYuG42/3n7h1m55/rVd1s6XvshnNPUYG8O0o0iw+0F3fsipRXRb1yKw3eKWeejF8ljQY8C0mQX//8aMuDHDHnjutnaDJNlHi3/lmfXLjrwGIoOPMaz65slXehoIl4kj2k0iQR+xu82Zso6jD31o1CKvt8tFTXuEk8e63LqVF/HYSY5zY1zNNkjr6YSSrUy4uBbci4nIGhJW0FAtbVFO0uFlEzJY62b12XNWa19A7lHeP8ybCDiTayvH34ITXqal7zg9xBsYyZ5LJXdv+7m79O6eZ2Ho9PkAn5PFTfhQ01+t9GROsHDyzhzrzGTIJXK7h93BmcrgslOjSQAAbZZLHehcQ9fhf+lJwo7FF856YebVEGhrrGh8Q6roZJ+5AOYSZBKaffPsjPYbrSQjjHyF79n/B3Yuv57LFmyxPP2i5r8xWp8f1DzAVIVjQtKBJMm2ARK+L1GZ81qrIZK6tBKTS7i6LdYRG4Dvg80AZ8CP1VK7YjtuxaYDLQCU5VS/3Q4Vsfkoi1eh3Daw2ydfbvHe83Xs6/M26JxGuc4nb68AlyrlGoRkVuBa4GrRWR/4BzgAKA/8KqI7KuUyk4H6hzmpcihHTfM+MCfgQSMPiVi2t5sps6+k+OzQZBFP2h1kjSdcST8Sqn5Cd8uBM6MfR4HPK6UagQ+E5E1wGjgXTPX7VEJ2/OrLpQpevCV30MILEax5kaZsmbr7Ns9XhNcv4hmN24aLCcBT8Q+DyD6IohTFdvWCRGZAkwBGDx4MABzZ3QelhWH74rFPw+VWSd5Ft+mFJPeq2JNbRONbYoJQ7szdURvn0aXW1itJZ+NuvxtOzYhXbq2C2XTu0+FWii1XyT4ZPwfEZFXAaOed9crpZ6PHXM90ALMiZ9mcLzhOlwpNQOYATBq1ChXorzCJPpGFIgwc8wgv4eRk1itJW/leLsmjlwVyqD5RTS7yfgbppT6brr9IjIROA04XikVF+4qIFG5BkKnfg6hxKg8gg4/1YBzE0cuCWUQ/SKa3Tgq2SAiJwNXA6crpb5O2DUPOEdEuojIMGA4sMjJvYJAqggaHVmjAWeloHNJKLVfJPg4XVPeC3QBXhERgIVKqQuVUitF5ElgFVET0C+dRvS47fB1s7CZkU/CEuPdGYcmGFgOFbUplKqlmV13nUfxMRMynpfNapm6X3HwcRrVs0+afdOB6U6un0gqcdVmFk2QsDNztyOUZl8W232oh+N1T16Nc0LvRbKzEgicaaayF9RstXeeJjDYnbnbEUo9q9Y4IfTC79jMEgT+/C+/R5DXuFW7P5tirGfVGifkgGpqNM5oXvKCKyKqxVgTFvKqEYtGY4QWa02+oYVfo9HYxm60kO7I6y/a1KPJWawUbjNDYmZuxfUvuXZdL4nXK+pTIp70ztX9eMOJFn5NzmK2cJtZEjNzw4abL0BN+NHCr9GYJLGmjmpuQoqKfRyNRmMfbePXaCyiGndRN/0UWjd+ZLh/+4RKXxKnNBqzaOHX5BVOSxfkUk0dTf6iTT2avCKVM9KM7d+L4mO6W5XGD7TwazQm8SIzV3er0viBFn6NxiReZObaacJSO/0UvTrQOELb+DWaABAv5dzl1KkZj624/iW6nHoJDc/8Pgsj0+QiWvg1Gp+x5TDOoRaNmuyjhV+j8RE7DmMrqwONxgg9ZdBofMSOw1iHk2qcooVfo8G9uj5W8wTsOIx1L1uNU7TwazSEq9hY0ztP6K5bGkdo4ddoQkbFdf/wewiakKOduxqNRzgtD6HReIWe8Ws0HpFsPnJSEtop+iWkSUSUCk6dbhHZAqzPcFhv4KssDCdb6OcJNq49T7c/fXpIQUUvXyZbO87vvjT2Uf//BBu7zzNEKbWH2YMDNeM3M3ARWaKUGpWN8WQD/TzBxqvn6fFoTVZnXPFn0P8/wSZbz6Nt/BqNRpNnaOHXaHKfTX4PQBMsAmXqMUmu1azVzxNsQvE82ydUmvXehuJ5LKCfxwaBcu5qNPmC2zZ+C8Kv0WhTj0bjE26aX7QpR2MJPePXaDSaPCMUM34R+a2IfCAiy0Rkvoj0j20XEblbRNbE9h/q91jNICK3ichHsTE/KyLdE/ZdG3uej0XkJD/HaRYROUtEVopIm4iMStoXuucBEJGTY2NeIyLX+D0eO4jIwyKyWURWJGzrKSKviMgnsX97+DlGs4jIIBH5l4h8GPtd+5/Y9lA+D4CIlIjIIhFZHnumm2Lbh4nIe7FnekJEil2/uVIq8F9At4TPU4H7Y59PBV4CBBgDvOf3WE0+z4lAYezzrcCtsc/7A8uBLsAw4FMg4vd4TTzPN4ARwBvAqITtYX2eSGysewHFsWfY3+9x2XiOscChwIqEbf8HXBP7fE38dy/oX8CewKGxzxXA6tjvVyifJzZeAcpjn4uA92I69iRwTmz7/cAv3L53KGb8SqmdCd+WAXH71DhgtoqyEOguIntmfYAWUUrNV0q1xL5dCAyMfR4HPK6UalRKfQasAUb7MUYrKKU+VEp9bLArlM9DdIxrlFJrlVJNwONEnyVUKKXeArYlbR4HzIp9ngX8v6wOyiZKqS+VUv+Jfa4FPgQGENLnAYjpVl3s26LYlwKOA56KbffkmUIh/AAiMl1EPgfOBX4d2zwA+DzhsKrYtjAxieiqBXLjeRIJ6/OEddxm6KuU+hKiYgr08Xk8lhGRocA3ic6QQ/08IhIRkWXAZuAVoivNHQkTQ09+9wIj/CLyqoisMPgaB6CUul4pNQiYA1wcP83gUoHwVmd6ntgx1wMtRJ8JQv48RqcZbAvE82QgrOPOeUSkHHga+N8kS0AoUUq1KqVGEl31jyZqNu10mNv3DUwCl1LquyYPnQv8A5hG9G04KGHfQOALl4dmi0zPIyITgdOA41XMmEeInycFgX2eDIR13GbYJCJ7KqW+jJlFN/s9ILOISBFR0Z+jlHomtjm0z5OIUmqHiLxB1MbfXUQKY7N+T373AjPjT4eIDE/49nTgo9jnecD5seieMUBNfNkXZETkZOBq4HSl1NcJu+YB54hIFxEZBgwHFiw/ctUAAAEXSURBVPkxRpcI6/MsBobHoiuKgXOIPksuMA+YGPs8EXjex7GYRkQEeAj4UCl1R8KuUD4PgIjsEY/oE5FS4LtEfRf/As6MHebNM/nt2Tbp/X4aWAF8ALwADEjwiv+JqF3svyRElAT5i6iT83NgWezr/oR918ee52PgFL/HavJ5fkB0ltxINJnon2F+nti4TyUaOfIpcL3f47H5DI8BXwLNsf+fyUAv4DXgk9i/Pf0ep8lnOZKoyeODhL+bU8P6PLFnOhh4P/ZMK4Bfx7bvRXSCtAb4G9DF7XvrBC6NRqPJM0Jh6tFoNBqNe2jh12g0mjxDC79Go9HkGVr4NRqNJs/Qwq/RaDR5hhZ+jUajyTO08Gs0Gk2e8f8BEsBxQPkTptsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3344d2f1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch:  0 | train loss: 0.0701 | test accuracy: 0.94\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3340189c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch:  0 | train loss: 0.1329 | test accuracy: 0.94\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f33401d2e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch:  0 | train loss: 0.0395 | test accuracy: 0.96\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f33504f0160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch:  0 | train loss: 0.0199 | test accuracy: 0.96\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3350563320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch:  0 | train loss: 0.1077 | test accuracy: 0.97\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3340435668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch:  0 | train loss: 0.0391 | test accuracy: 0.97\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f33503aa240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch:  0 | train loss: 0.0789 | test accuracy: 0.97\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f33504d67b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch:  0 | train loss: 0.1067 | test accuracy: 0.97\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f33402252e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch:  0 | train loss: 0.0277 | test accuracy: 0.97\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f334ff549b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch:  0 | train loss: 0.0251 | test accuracy: 0.98\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f33504c8470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# following function (plot_with_labels) is for visualization, can be ignored if not interested\n",
    "from matplotlib import cm\n",
    "try: from sklearn.manifold import TSNE; HAS_SK = True\n",
    "except: HAS_SK = False; print('Please install sklearn for layer visualization')\n",
    "def plot_with_labels(lowDWeights, labels):\n",
    "    plt.cla()\n",
    "    X, Y = lowDWeights[:, 0], lowDWeights[:, 1]\n",
    "    for x, y, s in zip(X, Y, labels):\n",
    "        c = cm.rainbow(int(255 * s / 9)); plt.text(x, y, s, backgroundcolor=c, fontsize=9)\n",
    "    plt.xlim(X.min(), X.max()); plt.ylim(Y.min(), Y.max()); plt.title('Visualize last layer'); plt.show(); plt.pause(0.01)\n",
    "\n",
    "plt.ion()\n",
    "# training and testing\n",
    "for epoch in range(EPOCH):\n",
    "    for step, (x, y) in enumerate(train_loader):   # gives batch data, normalize x when iterate train_loader\n",
    "        b_x = Variable(x)   # batch x\n",
    "        b_y = Variable(y)   # batch y\n",
    "\n",
    "        output = cnn(b_x)[0]               # cnn output\n",
    "        loss = loss_func(output, b_y)   # cross entropy loss\n",
    "        optimizer.zero_grad()           # clear gradients for this training step\n",
    "        loss.backward()                 # backpropagation, compute gradients\n",
    "        optimizer.step()                # apply gradients\n",
    "\n",
    "        if step % 100 == 0:\n",
    "            test_output, last_layer = cnn(test_x)\n",
    "            pred_y = torch.max(test_output, 1)[1].data.squeeze()\n",
    "            accuracy = (pred_y == test_y).sum().item() / float(test_y.size(0))\n",
    "            print('Epoch: ', epoch, '| train loss: %.4f' % loss.data[0], '| test accuracy: %.2f' % accuracy)\n",
    "            if HAS_SK:\n",
    "                # Visualization of trained flatten layer (T-SNE)\n",
    "                tsne = TSNE(perplexity=30, n_components=2, init='pca', n_iter=5000)\n",
    "                plot_only = 500\n",
    "                low_dim_embs = tsne.fit_transform(last_layer.data.numpy()[:plot_only, :])\n",
    "                labels = test_y.numpy()[:plot_only]\n",
    "                plot_with_labels(low_dim_embs, labels)\n",
    "plt.ioff()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[7 2 1 0 4 1 4 9 5 9] prediction number\n",
      "[7 2 1 0 4 1 4 9 5 9] real number\n"
     ]
    }
   ],
   "source": [
    "# print 10 predictions from test data\n",
    "test_output, _ = cnn(test_x[:10])\n",
    "pred_y = torch.max(test_output, 1)[1].data.numpy().squeeze()\n",
    "print(pred_y, 'prediction number')\n",
    "print(test_y[:10].numpy(), 'real number')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "tensor",
   "language": "python",
   "name": "tensor"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
